DHS COMPARATIVE REPORTS 43

Transcription

1 FACTORS ASSOCIATED WITH PRIOR TESTING AMONG HIV-POSITIVE ADULTS IN SUB-SAHARAN AFRICA DHS COMPARATIVE REPORTS 43 August 2016 This publication was produced for review by the United States Agency for International Development (USAID). The report was prepared by Sarah Staveteig, Sara K. Head, Trevor N. Croft, and Kathryn T. Kampa.

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3 DHS Comparative Reports No. 43 Factors Associated with Prior Testing among HIV-Positive Adults in Sub-Saharan Africa Sarah Staveteig 1 Sara K. Head 2 Trevor N. Croft 2 Kathryn T. Kampa 3 ICF International Rockville, Maryland, USA August The DHS Program, Avenir Health 2 The DHS Program, ICF International 3 Independent consultant Corresponding author: Sarah Staveteig, International Health and Development, ICF International, 530 Gaither Road, Suite 500, Rockville, MD 20850, USA; telephone: ; fax: ; sarah.staveteig@icfi.com

4 Acknowledgments: We thank Mary Mahy and Joy Fishel for their insightful reviews, Lynne Jennrich for editing, Natalie LaRoche for formatting, and Sam Estabrook and Matthew Pagan for production of maps. Editor: Lynne Jennrich Document Production: Natalie LaRoche Maps: Sam Estabrook and Matthew Pagan This study was carried out with support provided by the United States Agency for International Development (USAID) through The DHS Program (#AIDOAA-C ). The views expressed are those of the authors and do not necessarily reflect the views of USAID or the United States Government. The DHS Program assists countries worldwide in the collection and use of data to monitor and evaluate population, health, and nutrition programs. For additional information about the DHS Program contact: DHS Program, ICF International, 530 Gaither Road, Suite 500, Rockville, MD 20850, USA. Phone: ; Fax: ; Internet: Recommended citation: Staveteig, Sarah, Sara K. Head, Trevor N. Croft, and Kathryn T. Kampa Factors Associated with Prior Testing among HIV-Positive Adults in Sub-Saharan Africa. DHS Comparative Reports No. 43. Rockville, Maryland, USA: ICF International.

5 Contents Tables... v Figures... v Preface... vii Abstract... ix Abbreviations... xi 1. Background and Objectives Background Study Objectives Methods and Data HIV Serological Status and Prior Testing Weighting and Significance Testing Country Selection Estimated Knowledge of HIV Status; Adjustments Using Antiretroviral Therapy Coverage Covariates Examined Limitations HIV Prevalence and Testing Uptake HIV Prevalence in Focal Countries Uptake of HIV Testing by Serological Status Estimated Knowledge of HIV Status and Where to Get Tested Testing Uptake During Pregnancy and Birth Among HIV-positive Women Receipt of ANC and Uptake of HIV Testing During ANC Uptake at Birth, after Birth HIV Testing Uptake Among PLHIV Characteristics of the Population of PLHIV Factors Associated with Prior Testing Discussion and Conclusions References Appendix Tables iii

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7 Tables Table 2.1. Response rate and HIV prevalence... 7 Table 3.1. Uptake of HIV testing, by serological status and sex Table 3.2. ART coverage and estimated knowledge of HIV status Table 4.1. HIV testing among HIV-positive women during ANC Table 4.2. HIV testing among HIV-positive women, by date of last birth Table 5.1. Characteristics of PLHIV, by country Table A.1 Characteristics of HIV-negative adults, by country Table A.2. Characteristics of HIV-positive women, by country Table A.3. Characteristics of HIV-positive men, by country Table A.4. HIV testing among PLHIV, by sex and place of residence Table A.5. HIV testing among HIV-positive women, by age group Table A.6. HIV testing among HIV-positive men, by age group Table A.7. HIV testing among HIV-positive women age 15-49, by marital status Table A.8. HIV testing among HIV-positive men age 15-49, by marital status Table A.9. HIV testing among HIV-positive women age 15-49, by education Table A.10. HIV testing among HIV-positive men age 15-49, by education Table A.11. HIV testing among HIV-positive women age 15-49, by wealth Table A.12. HIV testing among HIV-positive men age 15-49, by wealth Table A.13. HIV testing among HIV-positive women age 15-49, by lifetime number of sexual partners Table A.14. HIV testing among HIV-positive men age 15-49, by lifetime number of sexual partners Table A.15. HIV testing among PLHIV, by self-report of STI symptoms in the past year Table A.16. HIV testing among HIV-positive women, by whether they gave birth in the past 2 years Table A.17. HIV testing among HIV-positive men, by whether they paid for sex in the past year Figures Figure 3.1. HIV prevalence in focal countries Figure 3.2. Estimated knowledge of HIV status (adjusted) among PLHIV Figure 3.3. Percentage of PLHIV who are estimated to know their HIV status (adjusted) by year and HIV prevalence Figure 3.4. Knowledge of where to get tested Figure 5.1. HIV testing among PLHIV, by sex Figure 5.2. HIV testing among PLHIV, by age group Figure 5.3. HIV testing among PLHIV, by place of residence Figure 5.4. HIV testing among PLHIV, by education Figure 5.5. HIV testing among PLHIV, by marital status Figure 5.6. HIV testing among PLHIV, by wealth quintile Figure 5.7. HIV testing among PLHIV, by number of lifetime sex partners Figure 5.8. HIV testing among PLHIV, by whether reported STI symptoms in the past year Figure 5.9. HIV testing among HIV-positive women, by whether given birth in the past 2 years Figure HIV testing among HIV-positive men, by whether they paid for sex in the past year v

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9 Preface The Demographic and Health Surveys (DHS) Program is one of the principal sources of international data on fertility, family planning, maternal and child health, nutrition, mortality, environmental health, HIV/AIDS, malaria, and provision of health services. One of the objectives of The DHS Program is to provide policymakers and program managers in low- and middle-income countries with easily accessible data on levels and trends for a wide range of health and demographic indicators. DHS Comparative Reports provide such information, usually for a large number of countries in each report. These reports are largely descriptive, without multivariate methods, but when possible they include confidence intervals and/or statistical tests. The topics in the DHS Comparative Reports series are selected by The DHS Program in consultation with the U.S. Agency for International Development. It is hoped that the DHS Comparative Reports will be useful to researchers, policymakers, and survey specialists, particularly those engaged in work in low- and middle-income countries. Sunita Kishor Director, The DHS Program vii

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11 Abstract With evidence on the benefits of the early diagnosis of HIV and the initiation of antiretroviral therapy (ART) mounting, HIV testing is a primary entry point for the prevention of HIV transmission. In sub- Saharan Africa, the scale-up of affordable and readily available HIV testing and treatment has allowed the region to make notable progress in the prevention of HIV/AIDS. UNAIDS has recently proposed a set of ambitious targets that, if achieved, are predicted to end the AIDS epidemic by The targets, known as , call for 90 percent of all people living with HIV (PLHIV) to know their status, 90 percent of those to receive antiretroviral therapy (ART), and 90 percent of ART recipients to achieve viral suppression. This report focuses on the first 90 in the target, and seeks to answer four main questions. First, how does testing uptake vary by serological status, sex, and country? Second, what proportion of PLHIV are estimated to know their status, and how does this vary by sex, country, timing of the survey, and size of the epidemic? Third, what is the role of maternal care in HIV testing uptake among HIV-positive women? And fourth, what background and behavioral characteristics are associated with ever being tested for HIV among PLHIV? This report analyzes data from Demographic and Health Surveys and AIDS Indicator Surveys fielded since 2006 in 15 sub-saharan African countries where voluntary serological testing was conducted: Cameroon, Congo (Brazzaville), Ethiopia, Gabon, Kenya, Lesotho, Malawi, Mozambique, Namibia, Rwanda, Swaziland, Tanzania, Uganda, Zambia, and Zimbabwe. In the countries studied, we find that between 23 percent and 71 percent of PLHIV are estimated to know their status; on average across countries, after adjusting for ART coverage, 51 percent of PLHIV are estimated to know their status. The results reflect encouraging progress, but the achievement is far short of the 90 percent goal set by UNAIDS for Several gaps in HIV testing coverage still exist, particularly among adolescents, rural residents, and the poorest. While the need continues to target demographic groups at greatest risk of HIV, additional interventions focused on reaching the most socially vulnerable populations are essential. ix

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13 Abbreviations AIS ANC ART CDC DHS ELISA HCT PLHIV PMTCT STI UNAIDS USAID WHO AIDS Indicator Surveys antenatal care antiretroviral therapy U.S. Centers for Disease Control and Prevention Demographic and Health Surveys enzyme-linked immunoassay HIV counseling and testing people living with HIV prevention of mother-to-child transmission sexually transmitted infection Joint United Nations Programme on HIV/AIDS U.S. Agency for International Development World Health Organization xi

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15 1. Background and Objectives In 2015, UNAIDS estimated 1.9 million new HIV infections annually among individuals age 15 and older. Of the estimated 36.7 million [34.0 million-39.8 million] 1 people living with HIV (PLHIV) worldwide, 25.5 million [23.0 million-28.3 million] are living in sub-saharan Africa, which globally is the region hardest hit by the epidemic (UNAIDS 2016b). The spread of affordable and readily available HIV tests and antiretroviral therapy (ART) in sub-saharan Africa has had a major impact on HIV prevention efforts. Individuals who know their status are less likely to engage in HIV-related risk behaviors (Fonner et al. 2012), and early ART for a person living with HIV can lead to a suppressed viral load, thereby reducing the risk of HIV transmission (UNAIDS 2014a). The number of AIDS-related deaths globally has fallen by 26 percent since 2010, from an estimated 1.5 million in 2010 to 1.1 million in 2015, an outcome directly related to the rapid increase in the number of people on ART (UNAIDS 2016d). Given the importance of testing and treatment to HIV prevention efforts, in 2014, UNAIDS proposed a series of ambitious targets known as : by 2020, 90 percent of all PLHIV will know their status, 90 percent of people diagnosed with HIV will receive ART, and 90 percent of people receiving ART will have viral suppression. UNAIDS predicts that achievement of these targets by 2020 will enable the world to end the AIDS epidemic by 2030, creating profound health and economic benefits (UNAIDS 2014a). This report focuses on the first 90 : HIV testing uptake and estimated knowledge of status among PLHIV in sub- Saharan Africa, and the factors associated with uptake among this population, by country Background The evolution of HIV treatment guidelines Before antiretroviral therapy (ART) was readily available, treatment guidelines drafted by the World Health Organization (WHO) used a conservative definition of treatment eligibility, including a required minimum CD4 cell-count threshold. As the availability of ART was scaled-up in the early 2000s and the effectiveness and multiple benefits of ART became better understood, the public health case for early initiation of ART strengthened considerably and the number and size of treatment programs increased (WHO 2015a). HIV treatment can prevent HIV-related illness, avert AIDS-related deaths, and prevent further transmission through viral suppression (UNAIDS 2014a). This transmission prevention potential influenced revisions to the WHO treatment guidelines and resulted in the recommendation of ART initiation for all people with diagnosed HIV infection, without the requirement of a prior CD4 test, also known as universal eligibility. Specific changes in the 2015 guidelines include recommended initiation of ART, regardless of CD4 cell count, and further recommendations on the use of oral pre-exposure prophylaxis among all populations at considerable risk of acquiring HIV (WHO 2015b). Universal eligibility for ART means that more people will start ART earlier than in previous years. As this expansion occurs, programs must continue to respond to the needs of all patients. The revised 2015 WHO recommendations to improve the quality and efficiency of services to PLHIV covers three areas: (1) the differentiated care framework to address the diverse needs of PLHIV; (2) alternative strategies for community delivery of ART to accommodate the growing number of people on ART; and (3) principles for improving the quality of care and providing people-centered care. 1 Confidence intervals are given in brackets following estimates. 1

16 Prior research on factors influencing HIV testing in sub-saharan Africa HIV testing uptake is not uniform across countries or communities in sub-saharan Africa. Various sociodemographic and sexual risk factors have been associated with uptake of HIV testing. Studies conducted in the region have identified several variables that may influence an individual s decision to seek or participate in HIV testing; these factors often include sex, residence, and education level. A 2013 analysis of HIV testing uptake in sub-saharan Africa found that in 23 of 29 countries, fewer men than women had ever been tested for HIV (Staveteig et al. 2013). The study found that a likely contributor to this discrepancy is the critical gateway to HIV testing and counseling that antenatal care (ANC) visits and other maternal health services provide for pregnant women, often through integrated opt-out provider-initiated testing and counseling. Higher percentages of urban residents, compared with rural residents, in sub-saharan Africa report ever having been tested for HIV. Factors such as accessibility of HIV testing services may play a role in these urban-rural disparities. The main reason for never having used facility-based testing and counseling services, as reported by participants in a Malawi study, was the distance to the testing center (Helleringer et al. 2009). Routine testing in hospitals and other health care facilities has significantly increased uptake and case finding among attendees of these facilities, but cost and convenience issues often limit the use of health care facilities among the lower socioeconomic strata in sub-saharan countries. Residents of these lower income households were significantly less likely to have ever used facility-based HIV testing services, compared to the rest of the population in Malawi (Helleringer et al. 2009). Education and knowledge also affect the likelihood of testing. Men and women who have attained secondary school or higher education are more likely to have ever been tested for HIV, compared with women with no education or women who have attended primary school only (Staveteig et al. 2013). Knowledge of HIV is related to the likelihood of having ever been tested; however, reverse causality is a distinct possibility. For example, inaccurate knowledge about HIV and ART was associated with non-use of HIV testing services in Tanzania. Participants in that study with a lower level of HIV knowledge were less likely to participate in the uptake of HIV testing; comparable outcomes were found among participants with poor ART knowledge. Uptake of HIV testing services was highest among participants with past HIV testing experience, compared to participants who never previously used testing services (South et al. 2013). Participation in high-risk sexual behavior and personal health concerns can also be motivating factors for testing, with concerns about ill health being more prominent among individuals that presented with a late seropositive diagnosis (Wanyenze et al. 2011). A study in Malawi found that participants with multiple sex partners over the last three years and participants who presented with recent symptoms of sexually transmitted infections (STIs) were more likely to participate in home-based testing and counseling (Helleringer et al. 2009). Similarly, a study in Zimbabwe found that the proportion of women tested for HIV was higher among women who reported more sexual partners. For men, higher odds of testing were noted only among men who had two lifetime sexual partners, compared with one lifetime sexual partner. Men in Zimbabwe who reported having an STI in the past 12 months were more likely to have been tested (Takarinda et al. 2016). A cross-national study found higher levels of testing among HIV-positive adults (Staveteig et al. 2013). HIV testing and treatment initiatives in sub-saharan Africa To increase HIV testing and treatment, several countries, including the 15 that this report focuses on, 2 have implemented initiatives with varying degrees of success. An estimated 60 percent [56%-65%] of PLHIV globally know their HIV status, and only 46 percent [43%-50%] of PLHIV are receiving ART, which makes 2 Cameroon, Congo (Brazzaville), Ethiopia, Gabon, Kenya, Lesotho, Malawi, Mozambique, Namibia, Rwanda, Swaziland, Tanzania, Uganda, Zambia, and Zimbabwe. 2

17 scaling-up access to testing and treatment services a major priority (UNAIDS 2016d). Finding effective, efficient ways to achieve scale-up has been an on-going challenge. One approach has been through the integration of prevention of mother-to-child transmission (PMTCT) programs with maternal and child health services. Rwanda, for example, began adopting a more familycentered approach in The approach included strategies designed to reach partners and other family members of pregnant women with HIV testing services. Methods that proved especially successful included strongly emphasizing counseling to encourage HIV testing, increasing the number of personnel at clinics when ANC services are being provided, adopting measures to streamline patient flows, cutting wait times, and assuring confidentiality. Uptake of HIV testing and PMTCT services among pregnant women rose to above 90 percent at the 18 clinics that implemented the new approaches, and, by 2009, more than 80 percent of male partners were also taking HIV tests, compared with 16 percent in 2003 (WHO 2015a). The incorporation of male partners of pregnant women attending ANC visits for HIV testing has also been highly encouraged in Swaziland, with official recommendations incorporated into the 2006 national HIV testing and counseling guidelines. Another successful and innovative PMTCT initiative, the Mother-Baby Pack, originated in Lesotho. Local health-care workers often found that pregnant women living with HIV were unable to make repeated trips to health facilities during and after pregnancy, mainly for reasons related to location and cost. To overcome this challenge, they would put medicines in plain brown envelopes for the women to take home and use throughout the duration of their pregnancy. In 2007, the Government of Lesotho included the minimum packs, as they were called at the time, in their national PMTCT strategy (Lesotho Ministry of Health 2012). The Mother-Baby Pack co-packages medications for use starting from 14 weeks of pregnancy until six weeks after the birth of the infant. To reduce potential stigma or involuntary disclosure, all women receiving ANC are provided one of three different types of packages: (1) for pregnant women who are HIV-negative, (2) for pregnant women who are HIV-positive and on prophylaxis, and (3) for pregnant women who are HIV-positive and on ART. A twelve-month implementation of the initiative was also planned and launched in Cameroon and Zambia in 2010, but due to concerns regarding quality service delivery and a growing need to assess community readiness, distribution of the packs ended early (UNICEF 2011). Mass testing campaigns have helped increase uptake among people who do not typically use healthcare services; this strategy has been particularly common in East African countries. Often, these campaigns use community-based testing, which is effective in reaching large numbers of first-time testers and diagnosing PLHIV at earlier stages of the disease. Ethiopia has implemented The Millennium AIDS Campaign as an innovative scale-up strategy, and the country has experienced a major increase in testing. In the pre-art era, fewer than half a million people were tested per year in the country; however, when the campaign began in 2006, that number increased to three million (Seyoum et al. 2009). Community health campaigns in Uganda aim to achieve universal testing across a community by removing significant barriers and offering rapid HIV testing. These campaigns offer HIV testing within broader service delivery, such as hypertension screening for adults and deworming of young children, and thereby normalizing HIV testing as a part of routine health care. Testing locations are also decentralized to minimize travel costs and waiting time, and community members are encouraged to attend, regardless of their perceived risk. Community health campaigns have been successful in identifying people who previously reported no prior testing (Chamie et al. 2014). Similar initiatives have been rolled out in Kenya, Namibia, Rwanda, and Zimbabwe (Embassy of the United States, Windhoek Namibia 2008; National AIDS and STI Control Programme (NASCOP) 2008; Rwanda Ministry of Health 2014; Takarinda et al. 2016). Additional community-based interventions targeting hard-to-reach populations that have proved effective include mobile testing sites and home-based testing and counseling. While Kenya has experienced an increase in availability of stand-alone HIV counseling and testing (HCT) centers, the services remained 3

18 concentrated in urban areas, and, in 2007, only 36 percent of adults age reported having been tested for HIV and received their results. To extend testing coverage to population groups with limited access to existing services, new delivery models have been developed. These new models put an emphasis on delivering services to rural and hardto-reach populations. This is accomplished through various mobile approaches using trucks, vans, tents, and existing community facilities, such as empty school rooms and churches. A 2010 study found that use of mobile HCT approaches resulted in greater uptake of HCT services in Kenya, with more than three times as many clients accessing HCT through mobile approaches than at stand-alone sites. The addition of community-site mobile HCT services was also found to be more cost effective than stand-alone sites (Grabbe et al. 2010). Kenya has also implemented home-based testing and counseling, along with Malawi, Mozambique, Tanzania, and Uganda. Members of households in the lowest income quartile in Malawi are significantly less likely to have ever used facility-based HCT services than the rest of the population. Providing home-based testing and counseling has the potential to drastically reduce existing socioeconomic gradients in HCT uptake and to help alleviate the impact of AIDS on the most vulnerable households (Helleringer et al. 2009). The incorporation of ambitious national targets has acted as a motivational strategy in countries such as Rwanda and Kenya; however, as these countries strive to achieve massive increases in HIV-related services in a relatively short time period, they also recognize that improvements in quality of care and health systems are equally important. Ethiopia, Mozambique, and Namibia have also made this a priority, and these countries have begun incorporating this aspect into their health-sector initiatives. One of Namibia s four primary health objectives, as described in the country s 2010 National Strategic Framework for HIV and AIDS, is health system strengthening to guarantee that the health system is capable of providing equitable, affordable, and high quality services, particularly to disadvantaged and marginalized populations in the country (WHO 2011). In Mozambique, a severe shortage of trained human resources and healthcare infrastructure inhibited early progress. In 2003, the government attempted to address these needs through the development of the National Health Sector Strategic Plan to Combat Sexually Transmitted Infections and HIV/AIDS for The document addressed the existing problems by including plans to train 2,000 intermediate-level healthcare professionals and, with the anticipation of a massive increase in ART coverage, developed a new national drug management and logistics system (WHO 2005). Overall, countries have been working with international partners to rapidly scale-up testing and treatment, but these services are part of a broader imperative to invest in strengthening and expanding health systems and infrastructure Study Objectives HIV testing is an entry point for efforts to reduce morbidity and mortality among PLHIV and prevent the transmission of HIV. In light of the recent targets, the present study seeks to answer four main questions for 15 sub-saharan Africa countries studied. First, how does testing uptake vary by serological status, sex, and country? Second, what proportion of the PLHIV population is estimated to know their status? How does knowledge vary by HIV prevalence and date of the survey? Third, what is the role of maternal care in HIV testing uptake among HIV-positive women? Fourth, what background and behavioral characteristics are associated with ever being tested for HIV among PLHIV? 4

19 2. Methods and Data 2.1. HIV Serological Status and Prior Testing Demographic and Health Surveys (DHS) and AIDS Indicator Surveys (AIS) are nationally representative, cross-sectional surveys conducted in countries worldwide. They are primarily funded by the U.S. Agency for International Development (USAID) and implemented with technical assistance from The DHS Program at ICF International. Surveys gather both individual and household interviews, as well as a number of biomarkers about health and wellbeing. In standard DHS and AIS surveys, respondents who say they have heard of HIV are asked, I don t want to know the results, but have you ever been tested for HIV? In earlier surveys, the term AIDS virus was used in place of HIV. If the respondent answers yes, they are asked a few subsequent questions timing, place of test, and, in some cases, whether testing was voluntary or required and then asked I don t want to know the results, but did you get the results of the test? (ICF International 2011, 2016). In three surveys Malawi 2010, Uganda 2011, and Namibia 2013 respondents who said they had ever been tested for HIV were subsequently asked about the results. In Namibia, the question was phrased as Have you ever been tested to see if you have HIV? In Malawi and Uganda, the term AIDS virus was used in place of HIV. If respondents answered yes, after intermediary questions on timing and location of the test, they were asked Did you get the results of the test? 3 Additionally, in the DHS and AIS surveys, respondents to the Woman s Questionnaire who have given birth in the two years before the survey are also asked separate but similar questions about HIV testing in the context of ANC and delivery services. If they were tested at any of these points in time they are skipped out of the question on ever testing, and instead proceed to questions about timing and receipt of results. The results of questions about ever testing and about testing during ANC and delivery described above are used to produce the two main indicators in this report: ever tested and tested in the last 12 months. As is standard for these indicators, the respondent must have received the results of the last test to be considered as having been tested. Respondents are asked additional questions about counseling before and after the test, but because these questions may be country-specific and subject to recall bias, we exclude questions about counseling and focus only on whether tested and received the results of the last test. Later on in the survey, after questions about past testing, in some DHS and in all AIS surveys, respondents are asked for consent to be anonymously tested for HIV. HIV testing undertaken during the survey process is separate from, and subsequent to, the self-reports of prior HIV testing in the questionnaire. It is possible, therefore, for respondents to be both HIV-positive and never tested for HIV; in other words, to have no knowledge of their HIV status at the time of the survey. HIV testing protocol in DHS and AIS surveys undergoes an ethical review by the host country, by ICF International, and for surveys receiving PEPFAR funding by the U.S. Centers for Disease Control and Prevention (CDC). After a participant consents to be tested, interviewers or a medical staff member accompanying the interviewers collects blood drops from a finger prick on filter paper. The collection, storage, and testing of these dried blood spot samples follow strict procedures to ensure quality and 3 Responses to questions about the prior test result among PLHIV in Uganda and Malawi have been analyzed elsewhere (Fishel, Barrère, and Kishor 2014). 5

20 reliability of the testing. 4 Each filter paper has a unique bar code that can be linked to the questionnaire to allow for analysis of HIV status by respondents background characteristics, but the bar code does not allow the results of the HIV test to be identified with the name or location of a specific individual. It sometimes happens that the Western blot results for a few samples are indeterminate; in such cases, the additional lab HIV testing algorithm used cannot definitively classify a sample as positive or negative. This happens in generally five or fewer cases per country. We exclude these respondents from the numerator and denominator of our sample, on the grounds that the objectives of this analysis require individuals to have a positive or negative classification. The number of indeterminates is too small to produce reliable estimates about this group, and, in fact, it is too low for their exclusion to influence the overall results. The difference is negligible, but occasionally our estimates of HIV prevalence differ by one-tenth of one percent from those presented online and in main DHS reports, which, as a general rule, group indeterminate results together with negatives Weighting and Significance Testing DHS and AIS surveys typically use a two-stage cluster sampling design to reach households and, ultimately, individuals, as described in the DHS Sampling and Household Listing Manual (ICF International 2012). Individual male and female HIV weights were applied to the data to adjust for nonresponse and to restore representativeness of the sample. Significance tests and confidence intervals presented in this report use complex survey commands in Stata, which adjust for sampling weights, stratification, and intra-cluster correlation. This report is primarily descriptive and does not conduct multivariate statistical tests, but 95 percent confidence intervals around most estimates are shown. When these confidence interval ranges (or, on charts, confidence bars) do not overlap, the difference is statistically significant at the p<.05 level; occasionally, bars can overlap, but the estimates are still statistically significantly different from each other. For that reason, statements of statistical significance in the text about figures for which only a confidence interval is shown were checked using logistic regressions with complex survey weights. Chapter 5 and the first three appendix tables show the composition of the HIV-positive and HIV-negative adult population by key characteristics. If sampling design aspects of the survey design could be ignored, tests of the null hypothesis that the HIV-positive and HIV-negative populations have the same composition on a categorical covariate could be done with a chi-square statistic. Since chi-square does not allow for complex survey adjustments, the tests of the null hypothesis that there is no association between the covariate and HIV status in this report are based instead on multinomial logit regressions, with the covariate as the outcome and HIV status as the independent variable. Our inferences are based on the p-values of the F statistics produced from these regressions Country Selection This report covers countries in sub-saharan Africa with a DHS or AIS survey conducted in 2006 or after that included HIV serological testing. We include only the most recent survey from a country if that survey included at least 100 men and 100 women who were classified as HIV-positive, according to the survey 4 The blood spots are dried overnight, packaged, and transported to a laboratory for testing. Although the standard DHS HIV testing protocol has recently changed, for the surveys included in this analysis, the following protocol was followed. In the laboratory, the samples were tested using an initial ELISA test, and then all positive samples and 5 to 10 percent of negative samples were retested with a second ELISA. For those tests with discordant results on the two ELISA tests, another test, usually a Western blot, was used to determine the result. As external quality control, all positive samples and a random sample of about 3 to 5 percent of the negative samples were sent to another lab not associated with the survey, and the testing protocol was repeated. The results from the independent lab were checked against the results of the main laboratory. 6

21 blood test, regardless of the overall HIV prevalence measured in the survey. Fifteen countries had surveys that qualified for inclusion. Table 2.1 shows the response rate, HIV prevalence, and sample size of HIV-positive adults for the surveys included in this report. Consent for HIV testing in the DHS or AIS survey ranged from 85.1 percent in Zimbabwe to 99.6 percent in Rwanda. We also show the weighted number of HIV-positive and HIVnegative adults in each survey. Table 2.1. Response rate and HIV prevalence Survey Number interviewed and eligible for serological testing a Adults age Consented to testing a (%) Tested, valid results b HIV prevalence b (%) Number b HIVpositive Number b HIVnegative Cameroon , , ,917 Congo (Brazzaville) , , ,726 Ethiopia , , ,854 Gabon , , ,018 Kenya , , ,286 Lesotho , , ,435 4,384 Malawi , , ,442 12,144 Mozambique , , ,039 8,022 Namibia , , ,085 6,646 Rwanda , , ,937 Swaziland , , ,119 6,068 Tanzania , , ,837 Uganda , , ,436 18,120 Zambia , , ,704 24,155 Zimbabwe , , ,064 11,499 Survey Number interviewed and eligible for serological testing a Women age Consented to testing a (%) Tested, valid results b HIV prevalence b (%) Number b HIVpositive Number b HIVnegative Cameroon , , ,817 Congo (Brazzaville) , , ,172 Ethiopia , , ,412 Gabon , , ,142 Kenya , , ,350 Lesotho , , ,230 Malawi , , ,177 Mozambique , , ,543 Namibia , , ,367 Rwanda , , ,507 Swaziland , , ,378 3,046 Tanzania , , ,156 Uganda , , ,976 Zambia , , ,216 12,503 Zimbabwe , , ,295 6,018 (Continues) 7

22 Table 2.1 Continued Survey Number interviewed and eligible for serological testing a Men age Consented to testing a (%) Tested, valid results b HIV prevalence b (%) Number b HIVpositive Number b HIVnegative Cameroon , , ,100 Congo (Brazzaville) , , ,555 Ethiopia , , ,442 Gabon , , ,876 Kenya , , ,936 Lesotho , , ,154 Malawi , , ,967 Mozambique , , ,479 Namibia , , ,279 Rwanda , , ,430 Swaziland , , ,022 Tanzania , , ,681 Uganda , , ,144 Zambia , , ,487 11,652 Zimbabwe , , ,481 a Number interviewed and eligible and percentage consenting are unweighted. b Weighted with HIV sample weights Estimated Knowledge of HIV Status; Adjustments Using Antiretroviral Therapy Coverage Estimating self-knowledge of HIV status is difficult, particularly among PLHIV. When HIV-positive individuals are asked directly about the results of their most recent test, the data suggest substantial underreporting (Fishel, Barrère, and Kishor 2014). For this reason, an indirect measure of self-knowledge can be an appropriate proxy. The proxy for knowledge of HIV status among PLHIV in this analysis is based on self-reported information on prior HIV testing. Individuals who report never having been tested or having not received results of the most recent test are assumed not to know their HIV status. At the same time, individuals who were tested and received the result in the past 12 months are highly likely to know their current status. The percentage of PLHIV who are estimated to know their status, therefore, can be considered to range from a lower bound equal to the percentage of respondents who have been tested and received their test result in the past 12 months to an upper bound equal to the percentage of respondents who have ever been tested and received their test result. For these reasons, we compute people living with HIV who are estimated to know their status as the midpoint of this range between the percentage of adults ever tested and the percentage tested in the past 12 months. It is equivalent to the UNAIDS indicator people living with HIV who know their status used for survey data until 2015 (UNAIDS 2014b, 2015). We prefer the addition of the word estimated as actual knowledge of HIV status among respondents is unobserved. To add precision, the estimate can be adjusted for ART coverage among PLHIV. Specifically, ART coverage can be an alternate lower bound to testing in the past 12 months because everyone on ART can be assumed to know they are HIV-positive. If the percentage of adults on ART is higher than the percentage tested in the past 12 months, ART coverage is substituted as the low bound and the midpoint estimate is recalculated to produce people living with HIV who are estimated to know their status (adjusted). Our adjusted indicator is equivalent to the revised definition of people living with HIV who know their status first used by UNAIDS in 2015 and officially introduced in 2016 (UNAIDS 2015, 2016c). 8

23 None of the 15 surveys in this analysis included a biomarker for ART use. Instead, the data source on ART coverage for countries surveyed in 2010 and after is the UNAIDS AIDSinfo website, with the indicator coverage of people receiving ART from the year of the survey fieldwork (UNAIDS 2016a). If survey fieldwork spanned two years, the estimate for ART coverage in the earlier year was used. Unpublished UNAIDS estimates of ART coverage from previous years were obtained through personal correspondence. 5 Note that estimates of ART coverage are for the entire adult population ages 15 and older, while survey analysis of PLHIV pertains only to adults age Covariates Examined The 10 covariates examined in this report reflect background characteristics that are associated with risk of HIV infection and with access to services, as well as behavioral characteristics and symptoms that elevate the risk of HIV infection and which may prompt individuals to seek out testing. The covariates are sex, place of residence, age group, marital status, educational attainment, wealth quintile, lifetime number of sex partners, self-reported STI symptoms in the past year, whether gave birth in the past two years (women), and whether paid anyone in exchange for sexual intercourse in the past year (men). Most covariates are self-explanatory, but a few deserve additional explanation. The term married includes both individuals who are married and those who are living with a partner as if married. Wealth quintile is based on principal components analysis of assets, amenities, and services at the household level and divided into quintiles of the household population. It is relative within surveys but not across countries; wealthier households may still be categorized as poor on an absolute basis. Self-reported STI symptoms applies to respondents who say they had a sexually transmitted infection or symptoms of an STI (a badsmelling, abnormal discharge from the vagina or penis or a genital sore or ulcer) in the 12 months preceding the survey Limitations While DHS and AIS survey data are high quality, this analysis has a few caveats. First, as discussed earlier, some non-standardization exists between survey rounds. The question on having been tested for HIV differs slightly; in early surveys, women and men were asked if they had ever been tested for the AIDS virus, and in later surveys they are asked if they have ever been tested for HIV. In three surveys Malawi, Namibia, and Uganda the question about HIV testing is not preceded with the phrase I don t want to know the results ; PLHIV who did not want to reveal their status may have been more inclined to state that they had never been tested. Questions on testing during ANC differ slightly across surveys. Second, this is a descriptive report of trends; multivariate tests of significance were not conducted. Patterns found in one dimension of HIV testing uptake, such as age, are almost inexorably linked to other factors, such as marital status and number of lifetime sexual partners. Third, national HIV testing and treatment programs have changed rapidly since the earliest survey in this study was conducted in Estimates from earlier surveys, Swaziland in particular, may not be representative of the situation today. Fourth, supplemental data on ART coverage from UNAIDS is useful for estimating the population of PLHIV who know their status, but it is drawn from other data sources that may not align perfectly with a nationally representative household survey. In particular, our estimates of ever and recently tested are limited to adults age 15-49, while ART coverage is measured among people ages 15 and older; coverage may be different among adults over age 50. Fifth, while population surveys have become important sources of HIV prevalence estimates, it is important to note that these estimates may include biases resulting from absence or refusal to participate or testing 5 Dr. Mary Mahy, message to first author, April 16,

24 error resulting in false positivity. In general, the higher the non-response, the greater the likelihood that the survey data may be inaccurate. Separating non-response resulting from absence and refusal is important in analyzing the effects of non-response on biomarker estimates. The 2015 UNAIDS/WHO guidelines on monitoring HIV impact using population-based surveys states that a non-response rate greater than 25 percent is considered high, and the collected characteristics that may be related to non-response should be further assessed, with all related calculations included in the final survey report (UNAIDS 2015). As Table 2.1 shows, the consent rate for HIV testing ranged from 85.1 percent in Zimbabwe to 99.6 percent in Rwanda; results should be interpreted with caution but are not close to the UNAIDS/WHO level said to be of concern (75 percent). An analysis of detailed lab results from 20 DHS and AIS surveys by Fishel and Garrett (2016) indicates that it is likely that testing error associated with false positivity on the ELISA tests in the HIV testing algorithm is present to some degree in many of the surveys analyzed. The magnitude of bias associated with testing error could not be measured by this analysis; however, in many surveys, this bias is likely to fall within the bounds of the confidence interval for the HIV prevalence estimate. While refusal to be tested may be more common among those who have previously tested positive for HIV, the magnitude of refusal bias in HIV prevalence surveys appears to depend on the study protocol. It has been found that bias is greater when post-test counseling and the return of HIV test results is a prerequisite of study participation (Reniers et al. 2009), which it is not in DHS and AIS surveys. Overall, populationbased surveys, such as DHS and AIS, have been found to provide reliable, nationally representative direct estimates of HIV seroprevalence in countries with generalized epidemics. HIV prevalence data from population-based surveys can be useful in understanding the size and spread of the epidemic and in adjusting estimates from sentinel surveillance (Mishra et al. 2008). 10

25 3. HIV Prevalence and Testing Uptake This chapter examines the overall HIV prevalence in the 15 countries included in the report. It also examines recent HIV testing by HIV serological status, ART coverage, and, using UNAIDS guidelines, the percentage of PLHIV estimated to know their HIV status. We present the percentage of PLHIV who know where to get an HIV test among PLHIV who have never been tested for HIV HIV Prevalence in Focal Countries Figure 3.1 shows the national HIV prevalence among adults age in the 15 countries under study, at the time of their most recent survey. Table 2.1 lists the prevalence in percentages. Prevalence is highest in countries in Southern Africa, with more than 24 percent of adults infected with HIV in Swaziland and Lesotho and more than 10 percent infected in the five other countries under study in this region Malawi, Mozambique, Namibia, Zambia, and Zimbabwe. Countries in East Africa have more moderate prevalence, ranging from 1.5 percent in Ethiopia to 7.3 percent in Uganda. The three countries in Central and Western Africa Gabon, Cameroon, and Congo (Brazzaville) all have a prevalence of 4.3 percent or less. Figure 3.1. HIV prevalence in focal countries 11

26 3.2. Uptake of HIV Testing by Serological Status Table 3.1 presents HIV testing in the past 12 months and ever tested by HIV serological status for adults, women, and men. Unadjusted logistic regressions (not shown here) indicate that, with two exceptions for men (Gabon 2012 and Congo (Brazzaville) 2009), having ever been tested for HIV is statistically significantly higher among HIV-positive individuals than among HIV-negative individuals in all surveys. The magnitude of the difference tends to range between 10 to 20 percentage points. Having been tested in the past 12 months is also higher among HIV-positive individuals, compared with those who are HIVnegative, but the magnitude of the difference is not as great and the relationship is not as consistently significant. Individuals who tested HIV-positive at an earlier date are unlikely to keep testing repeatedly. In Cameroon, Kenya, Mozambique, and Swaziland countries that differ widely in HIV prevalence both ever and recent testing are significantly higher among PLHIV. In only one country do we see HIV-positive individuals significantly less likely to test have tested recently than individuals who are HIV-negative. In Lesotho, specifically, where HIV prevalence is 29.7 percent among women, HIV-positive women are less likely to have recently tested for HIV, compared with women who are HIV-negative. While this difference in recent testing could potentially be a cause for concern, it may also indicate individuals who have already been identified as HIV-positive more than a year before the survey and see no need to retest. As discussed earlier, survey respondents typically are not asked what their test result was, and questions about testing are prefaced with the phrase, I don t want to know the result. In three countries, however Malawi, Namibia, and Uganda individuals were asked about their test result, and questions about testing were not prefaced in this way. The difference in wording is subtle, but PLHIV who were aware of their status in the surveys in these three countries may have been less inclined to state that they had previously been tested. In most countries, women are substantially more likely than men to have ever tested for HIV, regardless of serological status. Except for Ethiopia and Rwanda, where women and men are tested at nearly equal levels, the percentage of women who have ever tested for HIV is 5 to 21 percentage points higher than for men. Gender patterns are not as evident for HIV testing in the past 12 months. In five countries Gabon, Lesotho, Mozambique, Swaziland, and Zimbabwe both HIV-positive and HIV-negative women are noticeably more likely than men to have recently tested for HIV than their male counterparts (8 percentage points or higher). Men appear to be more likely to have recently tested, compared with women in only one country, Rwanda, where 45 percent of HIV-positive men recently tested, compared with 37 percent of HIV-positive women. 12

27 Table 3.1. Uptake of HIV testing, by serological status and sex Among women and men age 15-49, percentage tested in the past 12 months and percentage ever tested for HIV a by serological status Adults (%) Women (%) Men (%) HIVpositive 95% CI HIVnegative 95% CI HIVpositive 95% CI HIVnegative 95% CI HIVpositive 95% CI HIVnegative 95% CI Percentage tested in the past 12 months Cameroon [26.5,34.7] 21.0 [19.8,22.1] 30.2 [25.4,35.0] 21.9 [20.4,23.4] 31.6 [24.2,39.0] 19.9 [18.5,21.4] Congo (Brazzaville) [8.4,17.5] 7.6 [6.9,8.3] 14.1 [7.9,20.2] 8.3 [7.2,9.4] 10.3 [3.3,17.3] 6.8 [5.9,7.8] Ethiopia [22.8,35.7] 20.4 [18.8,22.0] 29.4 [20.2,38.7] 20.0 [18.2,21.7] 28.9 [18.3,39.5] 20.9 [19.1,22.7] Gabon [26.3,37.5] 27.1 [25.4,28.7] 34.8 [28.0,41.6] 31.5 [29.4,33.7] 23.5 [12.2,34.8] 22.3 [20.1,24.5] Kenya [30.2,44.5] 25.5 [23.6,27.5] 38.2 [30.0,46.4] 28.6 [25.7,31.5] 35.4 [25.3,45.6] 22.0 [18.9,25.1] Lesotho [45.4,51.6] 47.7 [45.7,49.7] 51.2 [47.3,55.0] 59.8 [57.2,62.3] 43.4 [37.3,49.5] 35.2 [32.4,38.0] Malawi 2010 b b b b b b b b b 30.8 [24.0,37.6] 31.6 [29.6,33.5] Mozambique [15.9,22.0] 12.7 [11.3,14.2] 21.8 [18.2,25.3] 16.2 [14.2,18.1] 13.6 [9.4,17.9] 8.2 [6.9,9.6] Namibia [43.6,51.6] 43.4 [41.7,45.2] 47.9 [43.0,52.8] 49.4 [47.2,51.5] 47.2 [40.0,54.4] 37.3 [35.0,39.7] Rwanda [33.9,44.8] 37.3 [36.3,38.3] 36.5 [29.9,43.2] 37.9 [36.6,39.1] 45.1 [35.6,54.5] 36.6 [35.1,38.0] Swaziland [21.4,25.1] 13.0 [12.0,14.1] 26.8 [24.2,29.3] 19.5 [17.9,21.1] 16.7 [13.6,19.7] 6.5 [5.5,7.6] Tanzania [29.2,37.7] 28.3 [27.0,29.7] 34.3 [29.2,39.4] 30.0 [28.4,31.7] 31.8 [25.7,37.9] 26.3 [24.8,27.9] Uganda 2011 b b b b b b b b b 26.5 [22.3,30.8] 22.8 [21.4,24.3] Zambia [41.5,46.1] 41.8 [40.8,42.9] 45.1 [42.3,47.9] 46.5 [45.1,48.0] 41.8 [38.6,45.0] 36.8 [35.5,38.1] Zimbabwe [30.1,34.8] 27.6 [26.2,29.1] 35.3 [32.6,38.0] 34.5 [32.8,36.1] 27.6 [23.7,31.5] 20.1 [18.1,22.1] Percentage ever tested Cameroon [63.3,72.1] 44.8 [43.3,46.3] 69.4 [64.6,74.3] 50.0 [48.2,51.9] 63.9 [55.8,72.0] 38.9 [37.1,40.7] Congo 30.9 [24.4,37.4] 20.0 [18.9,21.0] 35.2 [26.3,44.1] 22.2 [20.6,23.8] 21.1 [12.7,29.6] 17.5 [16.2,18.9] (Brazzaville) 2009 Ethiopia [63.9,79.7] 36.4 [34.3,38.6] 72.5 [63.2,81.7] 35.3 [32.8,37.8] 70.3 [59.8,80.8] 37.8 [35.6,39.9] Gabon [65.3,78.9] 57.5 [55.9,59.2] 76.5 [69.3,83.7] 67.1 [64.7,69.6] 59.4 [46.9,71.9] 47.4 [45.0,49.7] Kenya [63.5,74.3] 48.7 [45.8,51.6] 73.5 [67.1,79.9] 56.5 [53.2,59.7] 58.6 [47.8,69.4] 39.9 [35.9,43.8] Lesotho [82.8,87.3] 70.6 [68.9,72.3] 91.1 [89.2,93.0] 79.7 [77.6,81.8] 73.4 [68.3,78.4] 61.2 [58.4,64.0] Malawi [71.6,77.3] 60.9 [59.5,62.3] 81.0 [77.8,84.1] 70.6 [69.0,72.2] 63.1 [57.5,68.7] 50.9 [48.9,52.8] Mozambique [34.6,42.9] 24.5 [22.2,26.8] 43.2 [38.6,47.8] 31.3 [28.4,34.2] 30.1 [23.8,36.3] 15.6 [13.6,17.6] Namibia [86.5,90.6] 67.9 [66.4,69.4] 92.8 [90.7,94.9] 77.3 [75.5,79.1] 81.2 [76.7,85.7] 58.3 [56.0,60.5] Rwanda [92.2,96.9] 79.9 [79.1,80.7] 95.9 [93.5,98.3] 82.2 [81.2,83.2] 91.8 [86.7,96.8] 77.2 [75.9,78.4] Swaziland [36.5,40.9] 22.6 [21.2,23.9] 44.0 [41.3,46.7] 31.9 [30.1,33.6] 28.8 [25.1,32.5] 13.2 [11.7,14.7] Tanzania [65.4,73.0] 55.0 [53.5,56.5] 73.4 [69.3,77.6] 61.8 [60.1,63.6] 60.9 [53.7,68.1] 46.9 [45.1,48.7] Uganda [66.4,72.5] 55.5 [54.0,57.0] 76.5 [73.3,79.8] 64.8 [63.1,66.6] 57.3 [52.3,62.4] 44.0 [42.3,45.8] Zambia [80.0,83.4] 67.9 [67.0,68.9] 88.0 [86.3,89.7] 76.9 [75.8,78.0] 72.3 [69.3,75.3] 58.3 [57.0,59.7] Zimbabwe [61.5,65.8] 45.6 [44.0,47.1] 71.0 [68.6,73.4] 55.9 [54.2,57.7] 51.4 [47.4,55.3] 34.2 [32.0,36.4] a Here and throughout the report, tested means tested and received results of the last test. b Due to a problem with the questionnaires for the Malawi 2010 Demographic and Health Survey and Uganda 2011 AIDS Indicator Survey, data on time since last HIV test are not available for some women; therefore, these estimates are omitted. 13

28 3.3. Estimated Knowledge of HIV Status and Where to Get Tested Table 3.2 lists three components used to calculate estimated knowledge of HIV status among PLHIV: (1) tested for HIV in the past 12 months, (2) ART coverage, and (3) ever tested for HIV, along with the percentage of PLHIV who are estimated to know their HIV status, both adjusted for ART coverage and unadjusted. By design, the adjusted estimates are similar to the unadjusted estimates. The largest difference between estimated knowledge due to adjustment is in Ethiopia, where half of HIV-positive adults were estimated to be on ART at the time of the survey; this increases estimated knowledge of HIV status from 51 percent to 57 percent. In Malawi and Uganda, where an issue with the questionnaires prevented the surveys from accurately measuring testing in the past 12 months among all women, only the adjusted numbers that provide estimates of knowledge of one s own status are available. Table 3.2. ART coverage and estimated knowledge of HIV status Tested in past 12 months Percentage of HIV-positive adults age On ART a Ever tested Estimated to know their HIV status b Estimated to know their HIV status, adjusted c Cameroon Congo (Brazzaville) Ethiopia Gabon Kenya Lesotho Malawi 2010 d d 50.1 Mozambique Namibia Rwanda Swaziland Tanzania Uganda 2011 d d 47.3 Zambia Zimbabwe a Data on antiretroviral therapy (ART) coverage is from independent UNAIDS estimates for adults ages 15 and over. See text for details. b Estimated to know their HIV status is computed as the midpoint between the percentage tested during the past 12 months and the percentage ever tested. c Estimated to know their HIV status, adjusted uses ART coverage as an alternate lower bound for knowledge of HIV status. If ART coverage is higher than the percentage tested in the past 12 months, then it is substituted as the lower bound for taking the midpoint with ever tested to estimate knowledge of HIV status. d Due to a problem with the questionnaires for the Malawi 2010 Demographic and Health Survey and Uganda 2011 AIDS Indicator Survey, data on time since last HIV test are not available for some women; therefore, these estimates are omitted. The percentage of PLHIV tested in the past 12 months ranges from 13 percent in Congo (Brazzaville) to 49 percent in Lesotho. The percentage of PLHIV ever tested ranges from 31 percent in Congo (Brazzaville) to 95 percent in Rwanda. In all, Congo (Brazzaville), Mozambique, and Swaziland report the lowest percentages of recent and ever tested among the countries under study. Less than a quarter of PLHIV in each country have recently tested, and less than 40 percent have ever been tested. Lesotho, Namibia, Rwanda, and Zambia report the highest levels of recent and ever tested, with ever tested each above 80 percent. In several countries, there is wide variation in the percentage recently and ever tested; in seven countries, the percentage of PLHIV who were recently tested is less than half of the percentage ever tested. 14

29 ART coverage estimated for the year of survey fieldwork ranges from 11 percent in Swaziland to 52 percent in Zambia. In eight countries, fewer than one-quarter of PLHIV were on ART at the approximate time the survey was conducted. Three of the four countries with the highest levels of recent and ever tested also report the highest percentage of adults on ART (Namibia, Rwanda, and Zambia: each 47 percent or greater). In Ethiopia, which fell mid-range for ever and recently tested, 41 percent of PLHIV were on ART. The adjusted percentage of adults estimated to know their HIV status ranges from 23 percent in Congo (Brazzaville) to 71 percent in Rwanda (Table 3.2 and Map 3.2). In 9 of 15 countries, more than one-half of adults are estimated to know their HIV-positive status. Even so, none of the countries under study have achieved the 90 percent target set by UNAIDS for 2020; the closest to that goal are four countries where estimated (adjusted) knowledge is just above two-thirds: Rwanda, Namibia, Zambia, and Lesotho. Figure 3.2. Estimated knowledge of HIV status (adjusted) among PLHIV 15